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Calculation of ATP production rates using the Seahorse XF Analyzer

  • Brandon R. Desousa
  • , Kristen K.O. Kim
  • , Anthony E. Jones
  • , Andréa B. Ball
  • , Wei Y. Hsieh
  • , Pamela Swain
  • , Danielle H. Morrow
  • , Alexandra J. Brownstein
  • , David A. Ferrick
  • , Orian S. Shirihai
  • , Andrew Neilson
  • , David A. Nathanson
  • , George W. Rogers
  • , Brian P. Dranka
  • , Anne N. Murphy
  • , Charles Affourtit
  • , Steven J. Bensinger
  • , Linsey Stiles
  • , Natalia Romero
  • , Ajit S. Divakaruni*
  • *Corresponding author for this work
  • University of California at Los Angeles
  • Agilent Technologies
  • Cytokinetics, Inc.

Research output: Contribution to journalArticlepeer-review

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Abstract

Oxidative phosphorylation and glycolysis are the dominant ATP-generating pathways in mammalian metabolism. The balance between these two pathways is often shifted to execute cell-specific functions in response to stimuli that promote activation, proliferation, or differentiation. However, measurement of these metabolic switches has remained mostly qualitative, making it difficult to discriminate between healthy, physiological changes in energy transduction or compensatory responses due to metabolic dysfunction. We therefore present a broadly applicable method to calculate ATP production rates from oxidative phosphorylation and glycolysis using Seahorse XF Analyzer data and empirical conversion factors. We quantify the bioenergetic changes observed during macrophage polarization as well as cancer cell adaptation to in vitro culture conditions. Additionally, we detect substantive changes in ATP utilization upon neuronal depolarization and T cell receptor activation that are not evident from steady-state ATP measurements. This method generates a single readout that allows the direct comparison of ATP produced from oxidative phosphorylation and glycolysis in live cells. Additionally, the manuscript provides a framework for tailoring the calculations to specific cell systems or experimental conditions.
Original languageEnglish
Number of pages0
JournalEMBO Reports
Volume0
Issue number0
Early online date7 Aug 2023
DOIs
Publication statusE-pub ahead of print - 7 Aug 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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